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LONDON, GREATER LONDON, UNITED KINGDOM, February 4, 2025 /EINPresswire.com/ -- The insurance fraud detection market has experienced significant growth in recent years. It is expected to expand from $7.5 billion in 2024 to $9.13 billion in 2025, with a compound annual growth rate (CAGR) of 21.6%. The growth in the past period can be attributed to the increasing occurrence of insurance fraud, the complexity of fraud schemes, regulatory compliance demands, customer security expectations, and the globalization of insurance markets.
How Big Is the Global Insurance Fraud Detection Market Expected to Grow, and What Is Its Annual Growth Rate?
The insurance fraud detection market is anticipated to experience rapid growth in the coming years. It is projected to reach $22.92 billion by 2029, growing at a compound annual growth rate (CAGR) of 25.9%. This growth can be attributed to the global adoption of data sharing platforms, increased regulatory focus on fraud prevention, improved insider threat detection, stronger identity verification measures, and heightened cybersecurity efforts. Key trends in the forecast period include the rise of advanced analytics and machine learning, partnerships with insurtech companies, a focus on real-time fraud prevention, digital identity verification, the use of geospatial data for risk assessment, and adherence to regulatory compliance and reporting requirements.
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What Is Driving the Growth of the Insurance Fraud Detection Market?
The increase in cyberattacks is expected to propel the growth of the insurance fraud detection market. A cyberattack is a dangerous and intentional attempt by an individual or organization to gain access to another person's or organization's data. Insurance companies are an excellent target for cyber-attacks since they have access to a large amount of personal policyholder data. Compared to other industries, which hold mainly sensitive financial data, insurers typically also collect a large amount of protected personal sensitive information.
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Which Leading Companies Are Driving The Growth Of The Insurance Fraud Detection Market Share?
Major companies operating in the insurance fraud detection market include ACI Worldwide Inc., BAE Systems PLC, BRIDGEi2i Analytics Solutions Pvt. Ltd., Datawalk Inc.
What Are The Key Trends Driving The Growth Of The Insurance Fraud Detection Market Size?
Technological innovations are a significant trend gaining momentum in the insurance fraud detection market. Numerous companies are introducing new solutions with enhanced technologies to better monitor and detect fraudulent insurance claims for their clients.
How Is the Global Insurance Fraud Detection Market Segmented?
The insurance fraud detection market covered in this report is segmented –
1) By Component: Solution, Services
2) By Organization Size: Small And Medium-Sized Enterprises (SMEs), Large Enterprises
3) By Deployment Type: On-Premises, Cloud
4) By Application: Claims Fraud, Identity Theft, Payment And Billing Fraud, Money Laundering
5) By End User: Insurance Companies, Agents And Brokers, Insurance Intermediaries, Other End Users
Subsegments:
1) By Solution: Fraud Analytics, Authentication Solutions, Governance, Risk, and Compliance (GRC) Solutions, Identity Verification Solutions, Predictive Analytics
2) By Services: Managed Services, professional services, Consulting Services, Training and Support Services, System Integration Services
The Leading Region in the Insurance Fraud Detection Market is:
North America was the largest region in the insurance fraud detection market in 2024.Asia-Pacific is expected to be the fastest-growing region in the forecast period.
What Is the Insurance Fraud Detection Market?
Insurance fraud detection involves identifying and preventing fraudulent activities related to money or insurance. Various software solutions are employed to analyze past patterns and incidents in order to predict future occurrences. Organizations typically use insurance fraud detection for fraud analytics, authentication, governance, risk management, and compliance to protect databases and identify potential vulnerabilities.
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